4.3 Article

Self-consistent residual dipolar coupling based model-free analysis for the robust determination of nanosecond to microsecond protein dynamics

期刊

JOURNAL OF BIOMOLECULAR NMR
卷 41, 期 3, 页码 139-155

出版社

SPRINGER
DOI: 10.1007/s10858-008-9244-4

关键词

dynamics; proteins; RDCs; structural noise; ubiquitin

资金

  1. NIGMS NIH HHS [GM 066041, R01 GM066041] Funding Source: Medline

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Residual dipolar couplings (RDCs) provide information about the dynamic average orientation of internuclear vectors and amplitudes of motion up to milliseconds. They complement relaxation methods, especially on a time-scale window that we have called supra-tau(c) (tau(c) < supra-tau(c) < 50 mu s). Here we present a robust approach called Self-Consistent RDC-based Model-free analysis (SCRM) that delivers RDC-based order parameters independent of the details of the structure used for alignment tensor calculation-as well as the dynamic average orientation of the inter-nuclear vectors in the protein structure in a self-consistent manner. For ubiquitin, the SCRM analysis yields an average RDC-derived order parameter of the NH vectors < S-rdc(2)> = 0: 72 +/- 0: 02 compared to < S-LS(2)> = 0.778 +/- 0.003 for the Lipari-Szabo order parameters, indicating that the inclusion of the supra-tau(c) window increases the averaged amplitude of mobility observed in the sub-tau(c) window by about 34%. For the beta-strand spanned by residues Lys48 to Leu50, an alternating pattern of backbone NH RDC order parameter S-rdc(2) (NH) = (0.59, 0.72, 0.59) was extracted. The backbone of Lys48, whose side chain is known to be involved in the poly-ubiquitylation process that leads to protein degradation, is very mobile on the supra-tau(c) time scale (S-rdc(2) (NH) = 0.59 +/- 0.03), while it is inconspicuous (S-LS(2) (NH) = 0.82) on the sub-tau(c) as well as on mu s-ms relaxation dispersion time scales. The results of this work differ from previous RDC dynamics studies of ubiquitin in the sense that the results are essentially independent of structural noise providing a much more robust assessment of dynamic effects that underlie the RDC data.

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